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pro vyhledávání: '"Decker Thomas"'
Autor:
Decker, Thomas, Koebler, Alexander, Lebacher, Michael, Thon, Ingo, Tresp, Volker, Buettner, Florian
Monitoring and maintaining machine learning models are among the most critical challenges in translating recent advances in the field into real-world applications. However, current monitoring methods lack the capability of provide actionable insights
Externí odkaz:
http://arxiv.org/abs/2408.13648
Using feature attributions for post-hoc explanations is a common practice to understand and verify the predictions of opaque machine learning models. Despite the numerous techniques available, individual methods often produce inconsistent and unstabl
Externí odkaz:
http://arxiv.org/abs/2406.05090
Deep Learning has already been successfully applied to analyze industrial sensor data in a variety of relevant use cases. However, the opaque nature of many well-performing methods poses a major obstacle for real-world deployment. Explainable AI (XAI
Externí odkaz:
http://arxiv.org/abs/2310.12967
Concept-based explanation methods, such as Concept Activation Vectors, are potent means to quantify how abstract or high-level characteristics of input data influence the predictions of complex deep neural networks. However, applying them to industri
Externí odkaz:
http://arxiv.org/abs/2310.11450
Modern AI techniques open up ever-increasing possibilities for autonomous vehicles, but how to appropriately verify the reliability of such systems remains unclear. A common approach is to conduct safety validation based on a predefined Operational D
Externí odkaz:
http://arxiv.org/abs/2310.10635
Autor:
Decker, Thomas, Gross, Ralf, Koebler, Alexander, Lebacher, Michael, Schnitzer, Ronald, Weber, Stefan H.
In this paper, we investigate the practical relevance of explainable artificial intelligence (XAI) with a special focus on the producing industries and relate them to the current state of academic XAI research. Our findings are based on an extensive
Externí odkaz:
http://arxiv.org/abs/2310.07882
Publikováno v:
In Journal of Biological Chemistry October 2024 300(10)
Publikováno v:
In Renewable and Sustainable Energy Reviews February 2025 208
Autor:
Fasching, Peter A., Decker, Thomas, Hartkopf, Andreas, Nusch, Arnd, Heinrich, Bernhard J., Kurbacher, Christian, Fuchs, Roswitha, Tesch, Hans, Krabisch, Petra, Huober, Jens, Kuemmel, Sherko, Brucker, Sara, Janni, Wolfgang, Schneeweiss, Andreas, Schuler, Martin, Fehm, Tanja, Lüftner, Diana, Quiering, Claudia, Voges, Claudia, Kreuzeder, Julia, Reinisch, Mattea
Publikováno v:
In European Journal of Cancer February 2024 198